But what *is* a Neural Network? | Deep learning, chapter 1
🛈⏬Subscribe to stay notified about new videos: http://3b1b.co/subscribe Support more videos like this on Patreon: https://www.patreon.com/3blue1brown Or don't. It's your call really, no pressure. Special thanks to these supporters: http://3b1b.co/nn1-thanks Additional funding provided by Amplify Partners. For any early-stage ML entrepreneurs, Amplify would love to hear from you: 3blue1brown@amplifypartners.com Full playlist: http://3b1b.co/neural-networks Typo correction: At 14:45, the last index on the bias vector is n, when it's supposed to in fact be a k. Thanks for the sharp eyes that caught that! For those who want to learn more, I highly recommend the book by Michael Nielsen introducing neural networks and deep learning: https://goo.gl/Zmczdy There are two neat things about this book. First, it's available for free, so consider joining me in making a donation Nielsen's way if you get something out of it. And second, it's centered around walking through some code and data which you can download yourself, and which covers the same example that I introduce in this video. Yay for active learning! https://github.com/mnielsen/neural-networks-and-deep-learning I also highly recommend Chris Olah's blog: http://colah.github.io/ For more videos, Welch Labs also has some great series on machine learning: https://youtu.be/i8D90DkCLhI https://youtu.be/bxe2T-V8XRs For those of you looking to go *even* deeper, check out the text Deep Learning by Goodfellow, Bengio, and Courville. Also, the publication Distill is just utterly beautiful: https://distill.pub/ Lion photo by Kevin Pluck If you want to contribute translated subtitles or to help review those that have already been made by others and need approval, you can click the gear icon in the video and go to subtitles/cc, then add subtitles/cc . I really appreciate those who do this, as it helps make the lessons accessible to more people. Music by Vincent Rubinetti: https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown ------------------ 3blue1brown is a channel about animating math, in all senses of the word animate. And you know the drill with YouTube, if you want to stay posted on new videos, subscribe, and click the bell to receive notifications (if you're into that). If you are new to this channel and want to see more, a good place to start is this playlist: http://3b1b.co/recommended Various social media stuffs: Website: https://www.3blue1brown.com Twitter: https://twitter.com/3Blue1Brown Patreon: https://patreon.com/3blue1brown Facebook: https://www.facebook.com/3blue1brown Reddit: https://www.reddit.com/r/3Blue1BrownSpace Carving - Computerphile
🛈⏬Removing voxels until the shape emerges. Space Carving is a kind of virtual sculpture. Image Analyst Dr Mike Pound explains how though it's a bit rough and ready, it can be lightning fast. Rob Miles on Game Playing AI: https://youtu.be/5oXyibEgJr0 Deep Learning: https://youtu.be/l42lr8AlrHk Secure Web Browsing: https://www.youtube.com/watch?v=E_wX40fQwEA Thanks to Rick van de Zedde, Wageningen UR for kind permission to use their Tomato Seedlings footage. 3D Stereo Vision: https://youtu.be/O7B2vCsTpC0 Deep Learning: https://youtu.be/l42lr8AlrHk ISP Advert Injection / Secure Web Browsing: https://youtu.be/E_wX40fQwEA http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comMaze Solving - Computerphile
🛈⏬Putting search algorithms into practice. Dr Mike Pound reveals he likes nothing more in his spare time, than sitting in front of the TV coding. EXTRA BITS: https://youtu.be/kF7KlThoT9w Mike's Code: http://bit.ly/MikesMarvellousMazes http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comSo why do colliding blocks compute pi?
🛈⏬Solution to the block collision puzzle from last video. Special thanks to these viewers: http://3b1b.co/clacks-thanks Channel support comes from viewers, primarily via https://www.patreon.com/3blue1brown Many of you shared solutions, attempts, and simulations with me this last week. I loved it! Y'all are the best. Here are just two of my favorites. By a channel STEM cell: https://youtu.be/ils7GZqp_iE By Doga Kurkcuoglu: http://bilimneguzellan.net/bouncing-cubes-and-%CF%80-3blue1brown/ NY Times blog post about this problem: https://wordplay.blogs.nytimes.com/2014/03/10/pi/ The original paper by Gregory Galperin: https://www.maths.tcd.ie/~lebed/Galperin.%20Playing%20pool%20with%20pi.pdf I'm not sure if there is an original source fo the solution presented here since it's not the one from the Galperin paper. I found it independently, but certainly not first. I think it's the most natural approach one might take given the problem statement, as corroborated by the fact that one like this is referenced in the NYT wordplay blog linked above, as well as the fact that many solutions people sent my way in this last week had this flavor. If you want to contribute translated subtitles or to help review those that have already been made by others and need approval, you can click the gear icon in the video and go to subtitles/cc, then add subtitles/cc . I really appreciate those who do this, as it helps make the lessons accessible to more people. Music by Vincent Rubinetti. Download the music on Bandcamp: https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown Stream the music on Spotify: https://open.spotify.com/album/1dVyjwS8FBqXhRunaG5W5u ------------------ 3blue1brown is a channel about animating math, in all senses of the word animate. And you know the drill with YouTube, if you want to stay posted on new videos, subscribe: http://3b1b.co/subscribe Various social media stuffs: Website: https://www.3blue1brown.com Twitter: https://twitter.com/3blue1brown Reddit: https://www.reddit.com/r/3blue1brown Instagram: https://www.instagram.com/3blue1brown_animations/ Patreon: https://patreon.com/3blue1brown Facebook: https://www.facebook.com/3blue1brownConvolutional Neural Networks - The Math of Intelligence (Week 4)
🛈⏬Convolutional Networks allow us to classify images, generate them, and can even be applied to other types of data. We're going to build one in numpy that can classify and type of alphanumeric character and it will run in a Flask web app. Code for this video: https://github.com/llSourcell/Convolutional_neural_network Please Subscribe! And like. And comment. That's what keeps me going. More learning resources: https://github.com/dorajam/Convolutional-Network https://beckernick.github.io/neural-network-scratch/ https://adeshpande3.github.io/adeshpande3.github.io/A-Beginner%27s-Guide-To-Understanding-Convolutional-Neural-Networks/ http://cs231n.github.io/convolutional-networks/ http://deeplearning.net/tutorial/lenet.html https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/ https://www.youtube.com/watch?v=q555kfIFUCM&t=31s Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5wSecrets Hidden in Images (Steganography) - Computerphile
🛈⏬Secret texts buried in a picture of your dog? Image Analyst Dr. Mike Pound explains the art of steganography in digital images. The Problem with JPEG: https://youtu.be/yBX8GFqt6GA The Bayer Filter: https://youtu.be/LWxu4rkZBLw Super Computer & the Milky Way: https://youtu.be/5KEhhW8TOGk JPEG Discrete Cosine Transform (DCT): https://youtu.be/Q2aEzeMDHMA http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comThe True Power of the Matrix (Transformations in Graphics) - Computerphile
🛈⏬ The Matrix conjures visions of Keanu Reeves as Neo on the silver screen, but matrices have a very real use in manipulating 3D graphics. John Chapman explains the true power of the matrix. Graphics series with John Chapman: 1/ Universe of Triangles : http://youtu.be/KdyvizaygyY 2/ Power of the Matrix : http://youtu.be/vQ60rFwh2ig 3/ Triangles to Pixels : http://youtu.be/aweqeMxDnu4 4/ Visibility Problem : http://youtu.be/OODzTMcGDD0 5/ Light and Shade in Computer Graphics: Coming Soon John Chapman is a graphics programmer who blogs here: http://www.john-chapman.net How NOT to store Passwords: http://www.youtube.com/watch?v=8ZtInClXe1Q Addendum - at 12:35 the formula should read: x*0+y*0+1*1 http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computerphile is a sister project to Brady Haran's Numberphile. See the full list of Brady's video projects at: http://bit.ly/bradychannelsFinding the Edges (Sobel Operator) - Computerphile
🛈⏬Our eyes can spot edges with no problems, but how do computers determine what's an edge and what's not? Image Analyst Dr Mike Pound explains the Sobel Edge detector. How Blurs & Filters work: https://youtu.be/C_zFhWdM4ic The Problem with JPEG: https://youtu.be/yBX8GFqt6GA Secrets Hidden in Images (Steganography): https://youtu.be/TWEXCYQKyDc Man in the Middle Attacks: https://youtu.be/-enHfpHMBo4 Mike's Code in a zip file: http://bit.ly/computerphileEdge http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comMan in the Middle Attacks & Superfish - Computerphile
🛈⏬Lenovo sold thousands of computers all carrying the Superfish software. Tom Scott explains what a security nightmare this became. More Tom Scott: http://www.youtube.com/enyay http://www.twitter.com/tomscott CORRECTION: At 2min 46secs Tom says Private Key when he means Public Key - The private key is not shared. Chip & PIN Fraud: https://youtu.be/Ks0SOn8hjG8 Could We Ban Encryption?: https://youtu.be/ShUyfk4QB-8 How Blurs & Filters work: https://youtu.be/C_zFhWdM4ic Numberphile: Encryption & Huge Numbers : https://youtu.be/M7kEpw1tn50 Public Key Cryptography: https://youtu.be/GSIDS_lvRv4 http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comThe Uncertainty Principle and Waves - Sixty Symbols
🛈⏬Professor Philip Moriarty on uncertainty. Phil on Unmade Podcast: https://youtu.be/_cevGdtPyuk Phil's book: https://amzn.to/2OaeXSb More links and info below ↓ ↓ ↓ Patreon: https://www.patreon.com/sixtysymbols Previous uncertainty videos on Sixty Symbols: https://youtu.be/w3Nu1pSg1So https://youtu.be/D1yb1adU2vI https://youtu.be/dgoA_jmGIcA More Philip Moriarty on Sixty Symbols: http://bit.ly/Prof_Moriarty Visit our website at http://www.sixtysymbols.com/ We're on Facebook at http://www.facebook.com/sixtysymbols And Twitter at http://twitter.com/sixtysymbols This project features scientists from The University of Nottingham http://bit.ly/NottsPhysics Sixty Symbols videos by Brady Haran http://www.bradyharanblog.com Additional editing and animation by Pete McPartlan Email list: http://eepurl.com/YdjL9 Wrong Fourier is depicted - sorry Jean-Baptiste Joseph Fourier for showing François Marie Charles Fourier instead!What is a Monad? - Computerphile
🛈⏬Monads sound scary, but Professor Graham Hutton breaks down how handy they can be. https://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: https://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comConvolutional Neural Networks in Practice // Cassidy Williams, Clarifai (FirstMark's Code Driven)
🛈⏬Cassidy Williams, Software Engineer and Developer Evangelist at Clarifai, spoke at FirstMark's Code Driven NYC on April 13, 2016. Williams demonstrated how how Clarifai uses convolutional neural networks to build its powerful image recognition technology. Clarifai’s image recognition systems recognize various categories, objects, and tags in images, as well as find similar images. The company’s image recognition systems allow its users to find similar images in large uncategorized repositories using a combination of semantic and visual similarities. FirstMark Capital is an early stage venture capital firm based in New York City. Code Driven NYC is a community organized by FirstMark that brings together leading developers from across the tech ecosystem to learn, get inspired, and have fun. Join the group at http://www.meetup.com/Code-Driven-NYC/ or find out more at http://codedrivennyc.com/.-C- Programming Language: Brian Kernighan - Computerphile
🛈⏬ C is one of the most widely used programming languages of all time. Prof Brian Kernighan wrote the book on C , well, co-wrote it - on a visit to the University of Nottingham we asked him how it came about. Most Difficult Program - Ackermann Function: http://youtu.be/i7sm9dzFtEI Computer That Changed Everything - Altair 8800: https://youtu.be/6LYRgrqJgDc Factory of Ideas - Working at Bell Labs: https://youtu.be/QFK6RG47bww More from BWK on other computer languages at: https://www.youtube.com/watch?v=Sg4U4r_AgJU http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comA friendly introduction to Convolutional Neural Networks and Image Recognition
🛈⏬A friendly explanation of how computer recognize images, based on Convolutional Neural Networks. All the math required is knowing how to add and subtract 1's. (Bonus if you know calculus, but not needed.) For a brush up on Neural Networks, check out this video: https://www.youtube.com/watch?v=BR9h47JtqywEndianness Explained With an Egg - Computerphile
🛈⏬Byte ordering, or boiled egg orientation, endianness is important! Dr Steve Bagley on the computer science topic named after something from an 18th century novel.... The copy of Gulliver's Travels used in the graphics was found at archive.org and can be viewed here: http://bit.ly/C_Gulliver The animations of the hex to binary have a classic 'out by one' error - it occurred between keyboard and chair during the graphics creation process.... Sean https://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: https://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comOnion Routing - Computerphile
🛈⏬What goes on TOR stays on TOR, or so we hope. Dr Mike Pound takes us through how Onion Routing works. EXTRA BITS: https://youtu.be/6eWkdyRNfqY End to End Encryption: https://youtu.be/jkV1KEJGKRA Deep Web / Dark Web: https://youtu.be/joxQ_XbsPVw http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comNeural Network that Changes Everything - Computerphile
🛈⏬Years of work down the drain, the convolutional neural network is a step change in image classification accuracy. Image Analyst Dr Mike Pound explains what it does. Kernel Convolutions: https://youtu.be/C_zFhWdM4ic Deep Learning: https://youtu.be/l42lr8AlrHk Botnets: https://youtu.be/UVFmC178_Vs AI's Game Playing Challenge: https://youtu.be/5oXyibEgJr0 Space Carving: https://youtu.be/cGs90KF4oTc http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.com12a: Neural Nets
🛈⏬*NOTE: These videos were recorded in Fall 2015 to update the Neural Nets portion of the class. MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston In this video, Prof. Winston introduces neural nets and back propagation. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.eduWhere GREP Came From - Computerphile
🛈⏬Commonly used grep was written overnight, but why and how did it get its name? Professor Brian Kernighan explains. EXTRA BITS: https://youtu.be/bSaBe6WiC2s Inside an ALT Coin Mining Operation: COMING SOON Unix Pipeline: https://youtu.be/bKzonnwoR2I https://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: https://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comResizing Images - Computerphile
🛈⏬Nearest Neighbour and BiLinear resize explained by Dr Mike Pound Fire Pong: https://youtu.be/T6EBe_5LxO8 Google Deep Dream: https://youtu.be/BsSmBPmPeYQ FPS & Digital Video: https://youtu.be/yniSnYtkrwQ http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comAI's Game Playing Challenge - Computerphile
🛈⏬AlphaGo is beating humans at Go - What's the big deal? Rob Miles explains what AI has to do to play a game. What on Earth is Recursion?: https://youtu.be/Mv9NEXX1VHc Object Oriented Programming: https://youtu.be/KyTUN6_Z9TM Mixed Reality Continuum: https://youtu.be/V4qxfFPgqdc AI Playlist: AI Playlist: https://www.youtube.com/playlist?list=PLzH6n4zXuckoewGfo3a6ShFS3zPKndPd3 Many thanks to Nottingham Hackspace for providing the location and being downright awesome Easter Egg: https://youtu.be/B8CujhUwVic http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comDeep Learning - Computerphile
🛈⏬Google, Facebook & Amazon all use deep learning methods, but how does it work? Research Fellow & Deep Learning Expert Brais Martinez explains. EXTRA BITS from this Video: https://youtu.be/knVMp_xrOlo HTML: Poison or Panacea?: Coming Soon! AI's Game Playing Challenge: https://youtu.be/5oXyibEgJr0 Pong & Object Oriented Programming: https://youtu.be/KyTUN6_Z9TM Botnets: https://youtu.be/UVFmC178_Vs http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comHow Machines Learn
🛈⏬How do all the algorithms around us learn to do their jobs? **OMG PLUSHIE BOTS!!**: https://standard.tv/collections/cgp-grey/products/cgp-grey-sorterbot-5000-plush Bot Wallpapers on Patreon: https://www.patreon.com/posts/15959388 Footnote: https://www.youtube.com/watch?v=wvWpdrfoEv0 Podcasts: https://www.youtube.com/user/HelloInternetPodcast https://www.youtube.com/channel/UCqoy014xOu7ICwgLWHd9BzQ Thank you to my supporters on Patreon: James Bissonette, James Gill, Cas Eliëns, Jeremy Banks, Thomas J Miller Jr MD, Jaclyn Cauley, David F Watson, Jay Edwards, Tianyu Ge, Michael Cao, Caron Hideg, Andrea Di Biagio, Andrey Chursin, Christopher Anthony, Richard Comish, Stephen W. Carson, JoJo Chehebar, Mark Govea, John Buchan, Donal Botkin, Bob Kunz https://www.patreon.com/cgpgrey How neural networks really work with the real linear algebra: https://www.youtube.com/watch?v=aircAruvnKk Music by: http://www.davidreesmusic.comMagic -Nothing Up My Sleeve- Numbers - Computerphile
🛈⏬How are encryption standards constants chosen? Dr Mike Pound explains these not-so-magic numbers. http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comHow Convolutional Neural Networks work
🛈⏬A gentle guided tour of Convolutional Neural Networks. Come lift the curtain and see how the magic is done. For slides and text, check out the accompanying blog post: http://brohrer.github.io/how_convolutional_neural_networks_work.html Check out https://youtu.be/FmpDIaiMIeA for better audio and a more detailed account. Follow me for announcements: https://twitter.com/_brohrer_The Perfect Code - Computerphile
🛈⏬Summing up why Hamming's error correcting codes are regarded as 'Perfect' - Professor Brailsford explains. EXTRA BITS: https://youtu.be/i4zC67Yf5Iw For more background on this: https://youtu.be/1_X-7BgHbE0 http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comOptical Character Recognition (OCR) - Computerphile
🛈⏬OCR isn't just about scanning documents and digitizing old books. Explaining how it can work in a practical setting is Professor Steve Simske (Honorary Professor at the University of Nottingham as well as Director & Chief Technologist at HP Labs' Security Printing Solutions) http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comSilicon Brain: 1,000,000 ARM cores - Computerphile
🛈⏬The Human Brain Project is behind this attempt to build a million core brain simulator. Professor Steve Furber of the University of Manchester & one of the pioneers behind the original ARM chip, takes us through the SpiNNaker Project. How Computer Memory Works: https://youtu.be/XETZoRYdtkw Don Knuth on Email: https://youtu.be/QS8qwMna8_o Brian Kerninghan on Bell Labs: https://youtu.be/QFK6RG47bww C Programming Language: Brian Kernighan: https://youtu.be/de2Hsvxaf8M Steve Furber on BBC Micro: https://youtu.be/y4WG549i3YY Machine Learning: COMING SOON For more information on the Human Brain Project: http://bit.ly/computerphileHBP http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comDeep Learning - Computerphile
🛈⏬Deep Learning with Convolutional Neural Networks - Dr Mike Pound explains. CNN background: https://youtu.be/py5byOOHZM8 Onion Routing (TOR): https://youtu.be/QRYzre4bf7I https://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: https://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comDijkstra's Algorithm - Computerphile
🛈⏬Dijkstra's Algorithm finds the shortest path between two points. Dr Mike Pound explains how it works. How Sat Nav Works: https://youtu.be/EUrU1y5is3Y Slow Loris Attack: https://youtu.be/XiFkyR35v2Y http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comBitcoin Problems - Computerphile
🛈⏬Bitcoin may be doomed to failure as the blockchain struggles to scale up; Professor Ross Anderson from the University of Cambridge explains. EXTRA BITS - Bitcoin & Crime: https://youtu.be/ve0HbZ9NHb8 Computers Without Memory: https://youtu.be/vhiiia1_hC4 AI Safety: https://youtu.be/IB1OvoCNnWY How Bitcoin Works: https://youtu.be/JyxRH18YlpA http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comMachine Learning Methods - Computerphile
🛈⏬We haven't got time to label things, so can we let the computers work it out for themselves? Professor Uwe Aickelin explains supervised and un-supervised methods of machine learning. Silicon Brain: 1,000,000 ARM Cores: https://youtu.be/2e06C-yUwlc Brian Kerninghan on Bell Labs: https://youtu.be/QFK6RG47bww Could We Ban Encryption?: https://youtu.be/ShUyfk4QB-8 Computer That Changed Everything - Altair 8800: https://youtu.be/6LYRgrqJgDc http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comHow Deep Neural Networks Work
🛈⏬A gentle introduction to the principles behind neural networks, including backpropagation. Rated G for general audiences. Follow me for announcements: https://twitter.com/_brohrer_ Visit the blog: https://brohrer.github.io/how_neural_networks_work.html Get the slides: https://docs.google.com/presentation/d/1AAEFCgC0Ja7QEl3-wmuvIizbvaE-aQRksc7-W8LR2GY/edit?usp=sharingHill Climbing Algorithm & Artificial Intelligence - Computerphile
🛈⏬Audible free book: http://www.audible.com/computerphile Artificial Intelligence can be thought of in terms of optimization. Robert Miles explains using the evolution's algorithm. http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. See the full list of Brady's video projects at: http://bit.ly/bradychannelsQuantum Computing 'Magic' - Computerphile
🛈⏬Quantum Computing offers a potential sea-change in computer power, but what are the issues with it, why aren't we all using quantum iphones already? Associate Professor Dr Thorsten Altenkirch. Link to more information & Quantum IO Monad Code: http://bit.ly/Computerphile_QIOMonad *From Thorsten: We have updated the hackage package to work with the new monad library. If you want to play with QIO read the paper and download the code and then you can start quantum programming. :-) Public Key Cryptography: https://youtu.be/GSIDS_lvRv4 Cracking Windows by Atom Bombing: https://youtu.be/rRxuh9fp7QI Slow Loris Attack: https://youtu.be/XiFkyR35v2Y Google Deep Dream: https://youtu.be/BsSmBPmPeYQ http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comWhere HTML beats C? - Computerphile
🛈⏬The ultimate example of trouble from digital promiscuity. HTML is more tolerant than C because it has to be. Professor Brailsford explains. Deep Learning: https://www.youtube.com/watch?v=l42lr8AlrHk Secure Web Browsing: https://www.youtube.com/watch?v=E_wX40fQwEA AI Game Playing Challenge: https://www.youtube.com/watch?v=5oXyibEgJr0 Convolutional Neural Networks: https://www.youtube.com/watch?v=py5byOOHZM8 http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comColourspaces (JPEG Pt0)- Computerphile
🛈⏬Harry's: http://www.harrys.com/ use coupon code COMPUTERPHILE for $5 off What's a colourspace and why do we have different ones? It's horses for courses as Image Analyst Mike Pound explains. Digital Images: https://www.youtube.com/playlist?list=PLzH6n4zXuckpbNdFO2WW78evpMBqgqyp8 Atari ST: Pushing the Limits: https://youtu.be/3OdtfsXOkEY Professor Steve Furber on ARM: COMING SOON! Universe of Triangles: https://www.youtube.com/playlist?list=PLzH6n4zXuckrPkEUK5iMQrQyvj9Z6WCrm http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.com41 and more Ulam's Spiral - Numberphile
🛈⏬More on prime numbers and Ulam's Spiral - this time focusing on 41 and Arthur C. Clarke. More links & stuff in full description below ↓↓↓ This video features Dr James Clewett. More Clewett videos at: http://bit.ly/JamesClewett See our other Ulam Spiral video at: http://youtu.be/iFuR97YcSLM And more to come soon... The book discussed is The Garden of Rama. NUMBERPHILE Website: http://www.numberphile.com/ Numberphile on Facebook: http://www.facebook.com/numberphile Numberphile tweets: https://twitter.com/numberphile Subscribe: http://bit.ly/Numberphile_Sub Videos by Brady Haran Patreon: http://www.patreon.com/numberphile Brady's videos subreddit: http://www.reddit.com/r/BradyHaran/ Brady's latest videos across all channels: http://www.bradyharanblog.com/ Sign up for (occasional) emails: http://eepurl.com/YdjL9 Numberphile T-Shirts: https://teespring.com/stores/numberphile Other merchandise: https://store.dftba.com/collections/numberphileAlphaGo & Deep Learning - Computerphile
🛈⏬AlphaGo beat the Go World Champion 4-1. Why do the creators not know how? Brais Martinez is a Research Fellow & Deep Learning expert at the University of Nottingham. http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comGeneral Artificial Intelligence: Making sci-fi a reality | Darya Hvizdalova | TEDxTrencin
🛈⏬Darya Hvizdalova is a member of the international research & development company GoodAI which focuses on building a general artificial intelligence software program that will automate cognitive processes in science, technology, business and other fields. She speaks about how each of us can participate in the process. Darya is a member of the international research & development company GoodAI which focuses on building a general artificial intelligence software program that will automate cognitive processes in sceince, technology, business and other fields. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedxMobile Interface Problems - Computerphile
🛈⏬Mobile apps almost always use a 'stop to interact' model, Dr Joe Marshall takes us through the design problems of mobile interfaces. n.b. This was filmed before Niantic released Pokemon Go and therefore it is not included as an example. Swim Tracking App: https://youtu.be/-UxBdVirvJs Password Cracking: https://youtu.be/7U-RbOKanYs How not to store passwords: https://youtu.be/8ZtInClXe1Q Indie App Developer: https://www.youtube.com/playlist?list=PLzH6n4zXucko143CdpqH5AW6St02cxOjT http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comHTML IS a Programming Language (Imperative vs Declarative) - Computerphile
🛈⏬The professor took a lot of stick for calling HTML a programming language - here he shows why it can be described as a language, albeit a special purpose one. Where HTML beats C?: https://youtu.be/-csXdj4WVwA Most Difficult Program to Compute: https://youtu.be/i7sm9dzFtEI Cookie Stealing: https://youtu.be/T1QEs3mdJoc Deep Web & Dark Web: https://www.youtube.com/playlist?list=PLzH6n4zXuckpPcCIJigThQgx5CB5gPiC6 (Declarative) Haskell Example: https://youtu.be/EuWrAlKTkak http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comBitcoin, Blockchain Forks & Lightning - Computerphile
🛈⏬Discussing Bitcoin scaling - Mustafa Al-Bassam of the UCL Security group talks about on-chain and off-Chain ideas. UCL Link: http://bit.ly/C_UCL-people EXTRA BITS - What If... [[nb - this was recorded when there was a planned hard-fork for Bitcoin - which did not happen]] https://youtu.be/vGs6Ao_R3v0 https://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: https://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comBackpropagation Neural Network - How it Works e.g. Counting
🛈⏬Here's a small backpropagation neural network that counts and an example and an explanation for how it works, how it learns. A neural network is a tool in artificial intelligence that learns how to do things instead of be hand-coded. Recently it's been popularized with Google's deep dreaming neural network and Deepmind's AlphaGo beating world champion Lee Sedol at the game of go. My webpage with all the demo, neural network source code, and so on that I talked about is at: http://rimstar.org/science_electronics_projects/backpropagation_neural_network_software_3_layer.htm This video was made possible in part by support from: Jonathan Rieke James Padden Support RimstarOrg on Patreon https://www.patreon.com/user?u=680159 or make a one-time donation at http://rimstar.org/donate_support_rimstarorg.htm Subscribe so that you don't miss new videos as they come out http://www.youtube.com/user/rimstarorg?sub_confirmation=1 Go to the main channel page here https://youtube.com/rimstarorg See also: Does Volts or Amps Kill You? Voltage, Current and Resistance https://www.youtube.com/watch?v=9iKD7vuq-rY&list=PLFsZmHTZL-znMsTduihhoYU21XL-d3p3K How a Rocket Works/Earth to Space Eg SpaceX Falcon 9 and Dragon https://www.youtube.com/watch?v=L0AMQ6kRNMA&list=PL36D7ABECE2AC9666 How a Crystal Radio Works http://www.youtube.com/watch?v=0-PParSmwtE&list=PLFsZmHTZL-zlSltC6ELZW9PK4ks7wgPRz Follow behind-the-scenes on: Twitter https://twitter.com/#!/RimStarz Google+ https://plus.google.com/116395125136223897621 Facebook https://www.facebook.com/rimstarorg http://rimstar.org The Deep dream images were made using the Deep Dream Generator at: http://deepdreamgenerator.com/ The brain image was extracted from an animated GIF by Doctor Jana http://docjana.com/#/alzheimers https://creativecommons.org/licenses/by/4.0/deed.enConvolutional Neural Networks - Ep. 8 (Deep Learning SIMPLIFIED)
🛈⏬Out of all the current Deep Learning applications, machine vision remains one of the most popular. Since Convolutional Neural Nets (CNN) are one of the best available tools for machine vision, these nets have helped Deep Learning become one of the hottest topics in AI. Deep Learning TV on Facebook: https://www.facebook.com/DeepLearningTV/ Twitter: https://twitter.com/deeplearningtv CNNs are deep nets that are used for image, object, and even speech recognition. Pioneered by Yann Lecun at New York University, these nets are currently utilized in the tech industry, such as with Facebook for facial recognition. If you start reading about CNNs you will quickly discover the ImageNet challenge, a project that was started to showcase the state of the art and to help researchers access high-quality image data. Every top Deep Learning team in the world joins the competition, but each time it’s a CNN that ends up taking first place. A CNN tends to be a difficult concept to grasp. If you’ve ever struggled while trying to learn about these nets, please comment and share your experiences. CNNs have multiple types of layers, the first of which is the convolutional layer. To visualize this layer, imagine a set of evenly spaced flashlights all shining directly at a wall. Every flashlight is looking for the exact same pattern through a process called convolution. A flashlight’s area of search is fixed in place, and it is bounded by the individual circle of light cast on the wall. The entire set of flashlights forms one filter, which is able to output location data of the given pattern. A CNN typically uses multiple filters in parallel, each scanning for a different pattern in the image. Thus the entire convolutional layer is a 3-dimensional grid of these flashlights. Connecting some dots - A series of filters forms layer one, called the convolutional layer. The weights and biases in this layer determine the effectiveness of the filtering process. - Each flashlight represents a single neuron. Typically, neurons in a layer activate or fire. On the other hand, in the convolutional layer, neurons search for patterns through convolution. Neurons from different filters search for different patterns, and thus they will process the input differently. - Unlike the nets we've seen thus far where every neuron in a layer is connected to every neuron in the adjacent layers, a CNN has the flashlight effect. A convolutional neuron will only connect to the input neurons that it “shines” upon. The convoluted input is then sent to the next layer for activation. CNNs use backprop for training, but because a special engine called RELU is used for activation, the nets don’t suffer from the vanishing gradient problem. In real world applications, image convolution results in 100s of millions of weights and biases, which has an adverse effect on performance. Thus after RELU, the activations are typically pooled in an adjacent layer to reduce dimensionality. Afterwards, there is usually a fully connected layer that acts as a classifier. CNNs that are in use typically have an architecture with repeated sets of layers. Set 1 is a convolutional layer followed by a RELU. This set can be repeated a few times, and the repeated structure is followed by a pooling layer. This resulting combination forms set 2, which is also repeated a few more times. The final resulting structure is then attached to a fully connected layer at the end. This architecture allows the net to continuously build complex patterns from simple ones, all while lowering computing costs with dimensionality reduction. CNNs are a powerful tool, but there is one drawback – they require 10s of millions of labelled data points for training. They also must be trained with GPUs for the process to be completed in a reasonable amount of time. Credits Nickey Pickorita (YouTube art) - https://www.upwork.com/freelancers/~0147b8991909b20fca Isabel Descutner (Voice) - https://www.youtube.com/user/IsabelDescutner Dan Partynski (Copy Editing) - https://www.linkedin.com/in/danielpartynski Jagannath Rajagopal (Creator, Producer and Director) - https://ca.linkedin.com/in/jagannathrajagopalThe Game about Games - Computerphile
🛈⏬The game that shows people how games are made. Alex is an engineer at the National Videogame Arcade in Nottingham. Password Cracking: https://youtu.be/7U-RbOKanYs Gamer's Paradise: https://youtu.be/HZzdXR0bV8o The Indie Advantage (and criticism): https://youtu.be/iSg0F3hwMnE Computing Aladdin's Cave: https://youtu.be/zFb4tilDmBg Find out more about The National Videogame Arcade: @thenva http://www.gamecity.org http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.comThe Physics of Life: How Water Folds Proteins - with Sylvia McLain
🛈⏬Sorry about the audio problems for the first 30 seconds or so - stick with it, it levels out soon. Proteins are arguably the most important biological components in any living creature but only now are we beginning to look into the role water plays in their folding. Subscribe for regular science videos: http://bit.ly/RiSubscRibe From its effect on protein folding to its work as a universal solvent, the unique properties of water make it an indispensable ingredient for life. In this Discourse, Sylvia McLain will explore the fundamental and mysterious role of water in life. Sylvia McLain is a Research Lecturer in the University of Oxford's Department of Biochemistry. She investigates the role of water in protein folding and life. This Discourse was filmed in the Ri on Friday 25 February 2017. The Ri is on Twitter: http://twitter.com/ri_science and Facebook: http://www.facebook.com/royalinstitution and Tumblr: http://ri-science.tumblr.com/ Our editorial policy: http://www.rigb.org/home/editorial-policy Subscribe for the latest science videos: http://bit.ly/RiNewsletterComputer Generates Human Faces
🛈⏬5:51 To skip to the results. Standalone App: https://github.com/HackerPoet/FaceEditor/raw/master/FaceEditor.zip Source Code: https://github.com/HackerPoet/FaceEditor This is another fun project I came up with using the same data set as my other video. This time, I experiment with unsupervised learning to see what the computer can learn about faces, and try to generate some new ones.A Secret Code In Book Barcodes
🛈⏬A book's barcode may look like a bunch of random digits, but there is a secret mathematical code hidden in the barcode, which you can even use to perform a little magic trick to predict the last digit. Secret code in credit cards https://youtu.be/jSKNBtn1pUc Source https://en.wikipedia.org/wiki/International_Standard_Book_Number#Check_digits Subscribe: https://www.youtube.com/user/MindYourDecisions?sub_confirmation=1 Playlist to watch all videos on MindYourDecisions: https://www.youtube.com/playlist?list=UUHnj59g7jezwTy5GeL8EA_g This is the only channel to feature math topics suggested by people around the world. Support the channel on Patreon so we can share the beauty of mathematics and make the world a better place: https://www.patreon.com/mindyourdecisions If you buy from the links below I may receive a commission for sales. This has no effect on the price for you. Show your support! Get a mug, a t-shirt, and more at Teespring, the official site for Mind Your Decisions merchandise: https://teespring.com/stores/mind-your-decisions My Books The Joy of Game Theory shows how you can use math to out-think your competition. (rated 4.0/5 stars on 37 reviews) http://amzn.to/1uQvA20 The Irrationality Illusion: How To Make Smart Decisions And Overcome Bias is a handbook that explains the many ways we are biased about decision-making and offers techniques to make smart decisions. (rated 3.5/5 stars on 4 reviews) http://amzn.to/1o3FaAg Math Puzzles Volume 1 features classic brain teasers and riddles with complete solutions for problems in counting, geometry, probability, and game theory. Volume 1 is rated 4.4/5 stars on 13 reviews. http://amzn.to/1GhUUSH Math Puzzles Volume 2 is a sequel book with more great problems. (rated 4.5/5 stars on 6 reviews) http://amzn.to/1NKbyCs Math Puzzles Volume 3 is the third in the series. (rated 4/5 stars on 6 reviews) http://amzn.to/1NKbGlp 40 Paradoxes in Logic, Probability, and Game Theory contains thought-provoking and counter-intuitive results. (rated 4.4/5 stars on 13 reviews) http://amzn.to/1LOCI4U The Best Mental Math Tricks teaches how you can look like a math genius by solving problems in your head (rated 4.8/5 stars on 5 reviews) http://amzn.to/18maAdo Multiply Numbers By Drawing Lines This book is a reference guide for my video that has over 1 million views on a geometric method to multiply numbers. (rated 4.3/5 stars on 6 reviews) http://amzn.to/XRm7M4 Connect with me My Blog: https://mindyourdecisions.com/blog/ Twitter: https://twitter.com/preshtalwalkar Facebook: https://www.facebook.com/pages/Mind-Your-Decisions/168446714965 Pinterest: https://www.pinterest.com/preshtalwalkar/ Tumblr: https://preshtalwalkar.tumblr.com/ Instagram: https://instagram.com/preshtalwalkar/ Patreon: https://www.patreon.com/mindyourdecisions Newsletter (sent only for big news, like a new book release): http://eepurl.com/KvS0r

Inside a Neural Network - Computerphile

Just what is happening inside a Convolutional Neural Network? Dr Mike Pound shows us the images in between the input and the result. How Blurs & Filters Work (Kernel Convolutions): https://youtu.be/C_zFhWdM4ic Cookie Stealing: https://youtu.be/T1QEs3mdJoc Rob Miles on Game Playing AI: https://youtu.be/5oXyibEgJr0 Secure Web Browsing: https://www.youtube.com/watch?v=E_wX40fQwEA Deep Learning: https://youtu.be/l42lr8AlrHk http://www.facebook.com/computerphile https://twitter.com/computer_phile This video was filmed and edited by Sean Riley. Computer Science at the University of Nottingham: http://bit.ly/nottscomputer Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.com